Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis, S.G. Shaila; A Vadivel

Автор: Li Yan
Название: Handbook of Research on Innovative Database Query Processing Techniques
ISBN: 1466687673 ISBN-13(EAN): 9781466687677
Издательство: Mare Nostrum (Eurospan)
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Цена: 325250.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Focuses on database query processing methods, technologies, and applications. Aimed at providing an all-inclusive reference source of technologies and practices in advanced database query systems, this book investigates various techniques, including database and XML queries, spatiotemporal data queries, big data queries, metadata queries, and applications of database query systems.

Автор: Mathias Lux, Oge Marques
Название: Visual Information Retrieval Using Java and LIRE
ISBN: 1608459187 ISBN-13(EAN): 9781608459186
Издательство: Mare Nostrum (Eurospan)
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Цена: 41580.00 T
Наличие на складе: Невозможна поставка.
Описание: The critical introduction to this Broadview Edition gives particular emphasis to Wells`s hostility towards religion as well as his thorough knowledge of the Darwinian thought of his time. Appendices provide passages from Darwin and Huxley related to Wells`s early writing; in addition, excerpts from other writers illustrate late-nineteenth-century anxieties about social degeneration.

Автор: Pennington Diane
Название: Social Tagging for Linking Data Across Environments
ISBN: 1783303387 ISBN-13(EAN): 9781783303380
Издательство: Facet
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Цена: 109120.00 T
Наличие на складе: Нет в наличии.
Описание: This book, representing researchers and practitioners across different information professions, will explore how social tags can link content across a variety of environments.

Автор: Naresh Agarwal
Название: Exploring Context in Information Behavior: Seeker, Situation, Surroundings, and Shared identities
ISBN: 1681736098 ISBN-13(EAN): 9781681736099
Издательство: Mare Nostrum (Eurospan)
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Цена: 87780.00 T
Наличие на складе: Невозможна поставка.
Описание: Explores the many definitions and theoretical and empirical studies of context. The author attempts to map the conceptual space of context in information behaviour. The book proposes theoretical frameworks for mapping the boundaries, elements and variables of context. It further discusses how to incorporate these frameworks and variables in the design of research studies on context.

Автор: Binxing Fang, Yan Jia
Название: Groups and Interaction
ISBN: 3110597772 ISBN-13(EAN): 9783110597776
Издательство: Walter de Gruyter
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Цена: 107790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three volume set provides a systematic overview of theories and technique on social network analysis.Volume 2 of the set mainly focuses on the formation and interaction of group behaviors. Users’ behavior analysis, sentiment analysis, influence analysis and collective aggregation are discussed in detail as well. It is an essential reference for scientist and professionals in computer science.

Автор: Xiang Ren, Jiawei Han
Название: Mining Structures of Factual Knowledge from Text: An Effort-Light Approach
ISBN: 1681733927 ISBN-13(EAN): 9781681733920
Издательство: Mare Nostrum (Eurospan)
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Цена: 82230.00 T
Наличие на складе: Невозможна поставка.
Описание: The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora.Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-value mining and information extraction. This book introduces this new research frontier and points out some promising research directions.

Автор: Binxing Fang, Yan Jia
Название: Structure and Evolution
ISBN: 3110596067 ISBN-13(EAN): 9783110596069
Издательство: Walter de Gruyter
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Цена: 107790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three volume set provides a systematic overview of theories and technique on social network analysis. Volume 1 of the set mainly focuses on the structure characteristics, the modeling, and the evolution mechanism of social network analysis. Techniques and approaches for virtual community detection are discussed in detail as well. It is an essential reference for scientist and professionals in computer science.

Автор: Binxing Fang, Jia-Yan Yao
Название: [Set Online Social Network Analysis, Vol 1-3]
ISBN: 311062656X ISBN-13(EAN): 9783110626568
Издательство: Walter de Gruyter
Цена: 259100.00 T
Наличие на складе: Нет в наличии.

Автор: Zhai Chengxiang, Massung Sean
Название: Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
ISBN: 197000116X ISBN-13(EAN): 9781970001167
Издательство: Mare Nostrum (Eurospan)
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Цена: 85730.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

Автор: Zhai Chengxiang, Massung Sean
Название: Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
ISBN: 1970001194 ISBN-13(EAN): 9781970001198
Издательство: Mare Nostrum (Eurospan)
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Цена: 103210.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

Автор: Diane Rasmussen Pennington, Louise Spiteri
Название: Social Tagging in a Linked Data Environment
ISBN: 1783303395 ISBN-13(EAN): 9781783303397
Издательство: Facet
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Цена: 218240.00 T
Наличие на складе: Невозможна поставка.
Описание: This book, representing researchers and practitioners across different information professions, will explore how social tags can link content across a variety of environments.

Автор: Dan Wu, Shaobo Liang
Название: Mobile Search Behaviors: An In-depth Analysis Based on Contexts, APPs, and Devices
ISBN: 1681733013 ISBN-13(EAN): 9781681733012
Издательство: Mare Nostrum (Eurospan)
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Цена: 87780.00 T
Наличие на складе: Невозможна поставка.
Описание: With the rapid development of mobile Internet and smart personal devices in recent years, mobile search has gradually emerged as a key method with which users seek online information. In addition, cross-device search also has been regarded recently as an important research topic. As more mobile applications (APPs) integrate search functions, a user's mobile search behavior on different APPs becomes more significant. This book provides a systematic review of current mobile search analysis and studies user mobile search behavior from several perspectives, including mobile search context, APP usage, and different devices. Two different user experiments to collect user behavior data were conducted. Then, through the data from user mobile phone usage logs in natural settings, we analyze the mobile search strategies employed and offer a context-based mobile search task collection, which then can be used to evaluate the mobile search engine. In addition, we combine mobile search with APP usage to give more in-depth analysis, such as APP transition in mobile search and follow-up actions triggered by mobile search. The study, combining the mobile search with APP usage, can contribute to the interaction design of APPs, such as the search recommendation and APP recommendation. Addressing the phenomenon of users owning more smart devices today than ever before, we focus on user cross device search behavior. We model the information preparation behavior and information resumption behavior in cross-device search and evaluate the search performance in cross-device search. Research on mobile search behaviors across different devices can help to understand online user information behavior comprehensively and help users resume their search tasks on different devices.